```
require(stats)
(ii <- order(x <- c(1,1,3:1,1:4,3), y <- c(9,9:1), z <- c(2,1:9)))
## 6 5 2 1 7 4 10 8 3 9
rbind(x, y, z)[,ii] # shows the reordering (ties via 2nd & 3rd arg)
## Suppose we wanted descending order on y.
## A simple solution for numeric 'y' is
rbind(x, y, z)[, order(x, -y, z)]
## More generally we can make use of xtfrm
cy <- as.character(y)
rbind(x, y, z)[, order(x, -xtfrm(cy), z)]
## Sorting data frames:
dd <- transform(data.frame(x, y, z),
z = factor(z, labels = LETTERS[9:1]))
## Either as above {for factor 'z' : using internal coding}:
dd[ order(x, -y, z), ]
## or along 1st column, ties along 2nd, ... *arbitrary* no.{columns}:
dd[ do.call(order, dd), ]
set.seed(1) # reproducible example:
d4 <- data.frame(x = round( rnorm(100)), y = round(10*runif(100)),
z = round( 8*rnorm(100)), u = round(50*runif(100)))
(d4s <- d4[ do.call(order, d4), ])
(i <- which(diff(d4s[, 3]) == 0))
# in 2 places, needed 3 cols to break ties:
d4s[ rbind(i, i+1), ]
## rearrange matched vectors so that the first is in ascending order
x <- c(5:1, 6:8, 12:9)
y <- (x - 5)^2
o <- order(x)
rbind(x[o], y[o])
## tests of na.last
a <- c(4, 3, 2, NA, 1)
b <- c(4, NA, 2, 7, 1)
z <- cbind(a, b)
(o <- order(a, b)); z[o, ]
(o <- order(a, b, na.last = FALSE)); z[o, ]
(o <- order(a, b, na.last = NA)); z[o, ]
## Not run:
# ## speed examples for long vectors:
# x <- factor(sample(letters, 1e6, replace = TRUE))
# system.time(o <- sort.list(x)) ## 0.4 secs
# stopifnot(!is.unsorted(x[o]))
# system.time(o <- sort.list(x, method = "quick", na.last = NA)) # 0.1 sec
# stopifnot(!is.unsorted(x[o]))
# system.time(o <- sort.list(x, method = "radix")) # 0.01 sec
# stopifnot(!is.unsorted(x[o]))
# xx <- sample(1:26, 1e7, replace = TRUE)
# system.time(o <- sort.list(xx, method = "radix")) # 0.1 sec
# xx <- sample(1:100000, 1e7, replace = TRUE)
# system.time(o <- sort.list(xx, method = "radix")) # 0.5 sec
# system.time(o <- sort.list(xx, method = "quick", na.last = NA)) # 1.3 sec
# ## End(Not run)
```

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